Chen Qianyu, Zhang Yayun, Ye Langjie, Gong Shuai, Sun Hong, Su Guanyong
Jiangsu Key Laboratory of Chemical Pollution Control and Resources Reuse, School of Environmental and Biological Engineering, Nanjing University of Science and Technology, 210094 Nanjing, People's Republic of China.
Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, Jiangsu 210009, China.
Environ Int. 2021 Dec;157:106844. doi: 10.1016/j.envint.2021.106844. Epub 2021 Aug 26.
Lipidomic analysis has been proven to be a powerful technique to explore the underlying associations between xenobiotics and health status of organisms. Here, we established a strategy that combined the lipidomic analysis with high-throughput suspect contaminant screening technique with an aim to efficiently identify active xenobiotics in humans. Firstly, in the light of single liquid phase equilibrium of chloroform-methanol-water (15:14:2, v/v/v), we developed an efficient method that was able to simultaneously extract both polar and nonpolar lipids in serum samples. By use of this method, targeted and non-targeted lipid analyses were conducted for n = 120 serum samples collected from Wuxi city, China. Secondly, we established a suspect database containing 1450 contaminants that have been previously reported in human samples, and contaminants in this database were screened in the same batch of serum samples by use of high-resolution mass spectrometry (HR-MS). Thirdly, the underlying associations between suspect contaminants and lipids were explored and discussed, and we observed that levels of some lipids were statistically correlated with concentrations of numerous contaminants. Among these active contaminants, 23 ones were identified on the basis of HR MS and MS characteristics, and these contaminants belonged to the classes of phthalates, phenols, parabens, or perfluorinated compounds (PFCs). Three active xenobiotics were fully validated by comparison with authentic standards, and they were perfluorooctanoic acid (PFOA), perfluorooctane sulfonate (PFOS), and diethyl phthalate (DEP). There were statistically significant changes in levels of triglyceride (TG), lysophosphocholine (LPC), and sphingomyelin (SM) as peak areas of xenobiotics increase. We also observed that, among target lipid molecules, 18:0 lysophosphatidylethanolamine (LPE(18:0)) was very sensitive, and this lipid responded to exposure of various contaminants. Our present study provides novel knowledge on potential alteration of lipid metabolism in humans following exposure to xenobiotics, and provides an efficient strategy for efficiently identifying active xenobiotics in humans.
脂质组学分析已被证明是一种强大的技术,可用于探索外源性物质与生物体健康状况之间的潜在关联。在此,我们建立了一种将脂质组学分析与高通量可疑污染物筛选技术相结合的策略,旨在有效识别人体内的活性外源性物质。首先,根据氯仿 - 甲醇 - 水(15:14:2,v/v/v)的单相平衡,我们开发了一种能够同时提取血清样本中极性和非极性脂质的高效方法。使用该方法,对从中国无锡市收集的n = 120份血清样本进行了靶向和非靶向脂质分析。其次,我们建立了一个包含1450种先前在人类样本中报道过的污染物的可疑数据库,并使用高分辨率质谱(HR-MS)在同一批血清样本中筛选该数据库中的污染物。第三,探索并讨论了可疑污染物与脂质之间的潜在关联,我们观察到一些脂质水平与多种污染物浓度在统计学上相关。在这些活性污染物中,根据HR MS和MS特征鉴定出23种,这些污染物属于邻苯二甲酸盐、酚类、对羟基苯甲酸酯或全氟化合物(PFCs)类别。通过与标准品比较,对三种活性外源性物质进行了充分验证,它们是全氟辛酸(PFOA)、全氟辛烷磺酸(PFOS)和邻苯二甲酸二乙酯(DEP)。随着外源性物质峰面积增加,甘油三酯(TG)、溶血磷脂酰胆碱(LPC)和鞘磷脂(SM)水平存在统计学上的显著变化。我们还观察到,在目标脂质分子中,18:0溶血磷脂酰乙醇胺(LPE(18:0))非常敏感,这种脂质对各种污染物的暴露有反应。我们目前的研究提供了关于人类接触外源性物质后脂质代谢潜在改变的新知识,并提供了一种有效识别人体内活性外源性物质的有效策略。